Statistics for Six Sigma Green Belts with Minitab and JMP

Table of contents

1. Copyright
2. Acknowledgments
3. About The Author
4. Preface
5. Fundamentals of Six Sigma
   1. Introduction
   2. What is Six Sigma?
   3. Roles in A Six Sigma Organization
   4. Statistics and Six Sigma
   5. Learning Statistics for Six Sigma Using This Book
   6. Summary
   7. References
6. Introduction to Statistics
   1. Introduction
   2. Enumerative and Analytic Studies
   3. Types of Sampling
   4. Types of Variables
   5. Operational Definitions
   6. Summary
   7. References
   8. Appendix 2.1 Introduction to Minitab Version 14
   9. Appendix 2.2 Introduction to JMP Version 6
7. Presenting Data in Charts and Tables
   1. Introduction
   2. Graphing Attribute Data
   3. Graphing Measurement Data
   4. Summary
   5. References
   6. Appendix 3.1 Using Minitab to Construct Charts
   7. Appendix 3.2 Using JMP to Construct Charts
8. Descriptive Statistics
   1. Introduction
   2. Measures of Central Tendency
      1. Quartiles
   3. Measures of Variation
   4. The Shape of Distributions
      1. The Five-Number Summary
   5. Summary
   6. References
   7. Appendix 4.1 Using Minitab for Descriptive Statistics
   8. Appendix 4.2 Using JMP for Descriptive Statistics
9. Probability and Probability Distributions
   1. What is Probability?
   2. Some Rules of Probability
   3. The Probability Distribution
   4. The Binomial Distribution
      1. Characteristics of the Binomial Distribution
   5. The Poisson Distribution
   6. The Normal Distribution
   7. The Normal Probability Plot
   8. Summary
   9. References
   10. Appendix 5.1 Using Minitab for Probability Distributions and Plots
       1. Computing Normal Probabilities
   11. Appendix 5.2 Using JMP for Probability Distributions and Plots
       1. Computing Poisson Probabilities
10. Sampling Distributions and Confidence Intervals
    1. Sampling Distributions
       1. Sampling Distribution of the Mean
    2. Basic Concepts of Confidence Intervals
    3. Confidence Interval Estimate for The Mean (σ Unknown)
    4. Prediction Interval Estimate for A Future Individual Value
    5. Confidence Interval Estimate For The Proportion
    6. Summary
    7. References
    8. Appendix 6.1 Using Minitab to Construct Confidence Intervals
       1. Constructing the Confidence Interval Estimate for the Proportion
    9. Appendix 6.2 Using JMP to Construct Confidence Intervals
11. Hypothesis Testing
    1. Introduction
    2. Fundamental Concepts of Hypothesis Testing
       1. Risks in Decision Making Using Hypothesis-Testing Methodology
    3. Testing for The Difference Between Two Proportions
    4. Testing for The Difference Between The Means of Two Independent Groups
    5. Testing for The Difference Between Two Variances
       1. The F Test for the Ratio of Two Variances
    6. One-Way Anova: Testing for Differences Among The Means of Three or More Groups
       1. ANOVA Assumptions
       2. Levene’s Test for Homogeneity of Variance
    7. Wilcoxon Rank Sum Test for The Difference Between Two Medians
    8. Kruskal-Wallis Rank Test: Nonparametric Analysis for The One-Way Anova
    9. Summary
    10. References
    11. Appendix 7.1 Using Minitab for Hypothesis Testing
        1. Testing for the Difference Between Two Variances
        2. The Wilcoxon Rank Sum Test
    12. Appendix 7.2 Using JMP for Hypothesis Testing
12. Design of Experiments
    1. Introduction
    2. Design of Experiments: Background and Rationale
    3. Two-Factor Factorial Designs
    4. 2k Factorial Designs
    5. Fractional Factorial Designs
       1. Choosing the Treatment Combinations
    6. Summary
    7. References
    8. Appendix 8.1 Using Minitab for the Design of Experiments
    9. Appendix 8.2 Using JMP for the Design of Experiments
       1. Factorial Design
13. Simple Linear Regression
    1. Introduction
    2. Types of Regression Models
    3. Determining The Simple Linear Regression Equation
       1. Regression Model Prediction
    4. Measures of Variation
    5. Assumptions
    6. Residual Analysis
    7. Inferences About The Slope
       1. Confidence Interval Estimate of the Slope (β1)
    8. Estimation of Predicted Values
    9. Pitfalls in Regression Analysis
    10. Summary
    11. References
    12. Appendix 9.1 Using Minitab for Simple Linear Regression
    13. Appendix 9.2 Using JMP for Simple Linear Regression
14. Multiple Regression
    1. Introduction
    2. Developing The Multiple Regression Model
    3. Coefficient of Multiple Determination and The Overall F Test
    4. Residual Analysis for The Multiple Regression Model
    5. Inferences Concerning The Population Regression Coefficients
    6. Using Dummy Variables and Interaction Terms in Regression Models
    7. Collinearity
    8. Model Building
    9. Logistic Regression
    10. Summary
    11. References
    12. Appendix 10.1 Using Minitab for Multiple Regression
        1. Using Minitab for Dummy Variables and Interactions
    13. Appendix 10.2 Using JMP for Multiple Regression
15. Control Charts for Six Sigma Management
    1. Basic Concepts of Control Charts
    2. Control Limits and Patterns
    3. Rules for Determining Out-of-Control Points
    4. The p-Chart
    5. The c-Chart
    6. The u-Chart
    7. Control Charts for The Mean and Range
    8. Control Charts for The Mean and The Standard Deviation
    9. Individual Value and Moving Range Charts
    10. Summary
    11. References
    12. Appendix 11.1 Using Minitab for Control Charts
    13. Appendix 11.2 Using JMP for Control Charts
        1. and S-Charts
16. Review of Arithmetic and Algebra
    1. Part 1 Fill in The Correct Answer
    2. Part 2 Select The Correct Answer
    3. Symbols
    4. Exponents and Square Roots
    5. Equations
    6. Answers to Quiz
17. Summation Notation
    1. References
18. Statistical Tables
19. Documentation of Data Files
20. Glossary